2014 Bulletin

Bulletin vol. 28 no. 2 | 31 from MCI to AD. Of the proteins identified, inflammatory markers were among the most consistent predictors of conversion within their sample (Hye et al., 2014). Additional work by Mapstone and colleagues (2014) also found utility of plasma metabolites in identifying conversion of disease state. The ability for biomarkers to serve as a prognostic mechanism is significant for identifying those who need additional follow-up and treatment. This line of work will be valuable for patient enrichment in prevention trials (Henriksen et al., 2014). Recent work also suggests that the biomarker profile of AD varies according to ethnicity. Among non-Hispanic whites, the biomarker profile generated and cross-validated by our group was predominately inflammatory in nature (O'Bryant et al., 2010; 2011a; 2011b; 2014). However, in a recent study, we sought to evaluate the biomarker profile of AD among Mexican Americans. Serum proteomic markers were examined among 49 AD cases and 314 cognitively healthy controls with the overall algorithm yielding an AUC=0.88. Interestingly, the biomarker profile was heavily weighted towards metabolic markers among this group (O'Bryant et al., 2013b). Therefore, the blood-based work suggests that (1) the approach can be utilized to generate screening methods across ethnic groups and (2) the biological profile of AD may vary according to ethnicity and require different therapeutic options. Additional work by our group has sought to address the challenge of identifying early and very early AD stages, as this is a particularly challenging time point for current diagnostic methods; however, it is a critical time for treatment (Edwards et al., 2014a). By combining specific inflammatory blood-based serum biomarkers with select neurocognitive measures, early stages of AD could be identified with excellent accuracy (AUC= 0.91) (Edwards et al., 2014a). More recent work sought to extend before very early AD stages and reach pre-AD stages (i.e. MCI). Unpublished work from our groups looked at combining a serum panel of 21 biomarkers in distinguishing AD from MCI (Edwards et al., 2014b). The panel alone was found to discriminate disease presence by 69%. When examined by APOE4 status, the panel effectively identified 79% among non-carriers (Edwards et al., 2014b). When combined with a measure of semantic fluency, the overall accuracy of detection improved to 89% (Edwards et al., 2014b). This work provides further support for the utilization of serum biomarkers in combination with cognitive measures for improved diagnostic accuracy of AD and MCI. Use of blood-based biomarkers in the detection of AD, MCI, and other neurodegenerative disorders has significantly progressed over the past several years due to increased support for cost- effective, non-invasive, and affordable means of diagnostics. Current diagnostic means pose many barriers (financial, access to care) that blood-based biomarkers are able to effectively address. Our work, along with others, supports the use of blood- based biomarkers as a first step in a potentially multi-step process, which includes current diagnostic modalities, such as a neuropsychological evaluation. Arguably one of the fastest growing health concerns, AD poses a significant problem for society due to the estimated prevalence of the disease as well as limited means of effective diagnostics and treatment modalities. Significant work is needed in the area of MCI as well as among other neurodegenerative diseases. Current research supports the use of both serum and plasma biomarkers as a means of detecting disease presence; however, the relative consistency across research studies and findings are limited, which could be the result of unstandardized pre-analytic procedures (Henriksen et al., 2014; Snyder et al., 2014); however, the international working group recently published the first-ever guidelines for harmonization of methods across laboratories and cohorts (O'Bryant et al., 2014b). The current state of the literature suggests blood-based biomarker approaches hold potential for aiding in predicting risk for MCI and AD as well as screening for these cognitive disorders. Additional work is ongoing to determine if these approaches will be useful for screening procedures targeting cognitive loss associated with other conditions. These blood-based methods can also greatly facilitate new clinical trials by providing a means for patient identification and selection, patient stratification and identification of targeted subgroups most likely to benefit from specific interventions (Soares & Lovestone 2014; Henriksen et al 2014) as well as help identify those who require follow-up clinical diagnostics, including neuropsychological evaluations. Dr. Sid O'Bryant's laboratory studies factors related to cognitive loss during the aging process, particularly Alzheimer's disease. He is a global leader in the area of blood-based biomarkers of Alzheimer's disease and lead the international working group that recently generated the best practice guidelines for preanalytic methods in the research area. He has generated and cross-validated a blood-based screener for AD and, more recently, he has generated methods for identifying sub-populations of patients suffering from Alzheimer's disease so targeted (personalized) therapeutic approaches can be generated. His recent work has demonstrated how blood profiles vary across neurodegenerative diseases and he leads the newly generated Consortium for the Establishment of Biomarkers Across Neurodegenerative Diseases (CE-BAND). His work has been funded by the National Institute on Aging (NIA), Environmental Protection Agency (EPA), the State of Texas as well as numerous private foundations. He has published over 100 research articles and received multiple awards/honors including the early career award of the National Academy of Neuropsychology and the 2014 FABBS Early Career Impact Award.

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